ionews
Learn AI

Paths for every level

Organised by how much setup you're signing up for: no code means open a website and go, intermediate means some local setup, advanced means you're in deep. Costs are labelled honestly; the curricula stay free-first.

Open the glossary — every term, plainly defined

Suggested curricula

Pick the one that matches where you are. Durations are honest estimates, not marketing.

Get productive with chatbots, week one no code

Anyone — no code, no setup · ~1 week at 1 hr/day

From "I've heard of ChatGPT" to using AI competently for real daily work. The skill is delegation: knowing what to hand over and how to check it.

  1. Pick two assistants and make accounts — one general (ChatGPT, Claude, Gemini) + one for research (Perplexity); comparing two teaches more than mastering one
  2. Do real tasks, not demos — rewrite an email, summarise a contract, plan a trip, debug a spreadsheet formula — your actual work, every day
  3. Anthropic prompt engineering guide — read once, then apply: give context, show examples, ask for structure
  4. Learn the failure modes — hallucination, stale knowledge, confident nonsense — the glossary's "Using LLMs" section is your field guide
  5. Elements of AI, both parts — finish the week with real mental models under the habits

Programmer → ML practitioner intermediate

Comfortable with Python · ~4 months at 6–8 hrs/week

From writing ordinary code to training, fine-tuning, and deploying real models. Top-down first, then fill in the math.

  1. Kaggle Learn: pandas + intro ML — a weekend of warm-up if you haven't touched data tooling
  2. fast.ai Practical Deep Learning, part 1 — ship working models immediately; do the homework, not just the videos
  3. Karpathy — Zero to Hero — rebuild everything fast.ai gave you from scratch; this is where it clicks
  4. Hugging Face course — the practical open-model ecosystem: fine-tuning, datasets, deployment
  5. One personal project, shipped — train or fine-tune something on data you care about and put it online — an AI coding editor from the shelf above makes this faster

Practitioner → researcher-grade depth advanced

Finished the practitioner path or equivalent · ongoing, ~6+ months

Theory, current literature, and a specialisation. The free material here is as good as any degree — the scarce input is your consistency.

  1. Stanford CS224n or CS231n — pick by interest (language vs vision); do the assignments
  2. Deep Learning Book, selected chapters — read alongside the course wherever the math feels thin
  3. ARENA curriculum — if interpretability/safety pulls you; genuinely hands-on
  4. Reproduce one paper per month — the single habit that separates readers from researchers

Resource shelves

Chatbots & assistants — start using AI today no code 8

The most popular hosted assistants. Nothing to install: open the site, type, get work done. Every one of these has a meaningful free way in unless marked otherwise.

ChatGPT free tier — OpenAI's assistant and still the most-used chatbot on the web. Strong all-rounder; GPT-5.5 under the hood.
Claude free tier — Anthropic's assistant, known for long-document work, careful writing, and coding. Current flagship: Claude Fable 5.
Gemini free tier — Google's assistant, deeply wired into Search, Gmail, and Docs. Gemini 3.5 models with huge context windows.
Grok free tier — xAI's assistant with real-time X integration, voice, and image/video features built in (Grok 4.3).
DeepSeek free — Free chat on DeepSeek's open-weight frontier models (V4 line) — remarkable capability for the price of nothing.
Z.ai Chat (GLM-5.2) free tier — Consumer chat for Zhipu's GLM series; the paid GLM Coding Plan subscription is popular for agentic coding on a budget. (coding plans from ~$18/mo)
Microsoft Copilot free tier — Microsoft's consumer assistant across Windows, web, and mobile. See the Microsoft ecosystem page for the Office side.
Perplexity free tier — AI answer engine that cites its sources — the strongest choice when the task is research rather than conversation.
Foundations — understand what you're using no code 4

No programming required. These build correct mental models — the difference between using AI and being used by it.

Elements of AI free beginner — University of Helsinki's gentle, no-code introduction to what AI is and isn't. The best true starting point.
3Blue1Brown — Neural Networks series free beginner — Visual intuition for how neural networks and transformers actually work. Watch before touching any code.
Anthropic — Prompt engineering docs free all levels — Practical, vendor-documented techniques for getting reliable work out of LLMs; most of it transfers to any model.
Google Machine Learning Crash Course free beginner — Compact, practical ML fundamentals with interactive visualisations — the bridge toward the technical shelves below.
AI code editors & coding agents intermediate 6

Some local setup required — installing an editor or CLI and connecting an account. This is where AI stops answering questions and starts doing the work with you.

Cursor free tier — The AI-native VS Code fork that defined the category — inline edits, codebase chat, background agents, its own Composer models.
Google Antigravity free — Google's free agent-first development platform (IDE + CLI): Gemini-powered agents that plan, code, and test in a live browser.
Claude Code paid — Anthropic's terminal-based coding agent — reads your repo, edits files, runs commands. Built this site, as it happens. (Claude Pro/Max or API billing)
OpenAI Codex paid — OpenAI's coding agent across CLI, IDE extension, and cloud, including multi-day autonomous Goal Mode. (requires ChatGPT Plus or API key)
GitHub Copilot free tier — The IDE-extension route: completions and agent mode inside the editor you already use, with a real free tier.
Devin Desktop (formerly Windsurf) free tier — Cognition's VS Code-fork editor pairing a local agent with cloud agents that work while you don't. Renamed from Windsurf in June 2026.
For programmers — build with ML intermediate 5

Comfortable with Python? These take you from calling APIs to training and fine-tuning your own models.

fast.ai — Practical Deep Learning for Coders free intermediate — Top-down teaching: you train real models in lesson one and unpack the theory afterwards. The classic on-ramp.
Andrew Ng — Machine Learning Specialization free intermediate — The canonical bottom-up ML course: regression, classification, decision trees, best practices. (free to audit)
Andrej Karpathy — Neural Networks: Zero to Hero free intermediate — Build backprop, then a GPT, from scratch in raw Python/PyTorch. The single highest-signal free course on this list.
Hugging Face Course free intermediate — Working with transformers, fine-tuning, and the open-model ecosystem — straight from the people who run it.
Kaggle Learn free beginner — Bite-size, hands-on micro-courses: Python, pandas, intro ML — with in-browser notebooks, nothing to install.
Databases intermediate 5

Every AI application sits on one. SQLite for local work, Postgres when it grows up, pgvector when RAG arrives.

SQLBolt free beginner — Interactive SQL lessons in the browser — the fastest zero-setup way to learn queries. An hour here pays off for years.
SQLite — official docs & tutorial free beginner — A whole database in one file, no server — the right first database, and often the right last one.
PostgreSQL Tutorial free intermediate — Structured path through the leading open-source client-server database — what you graduate to when an app outgrows SQLite.
pgvector free intermediate — Embedding storage and similarity search inside Postgres — the pragmatic way to add RAG retrieval without a separate vector database.
DuckDB documentation free intermediate — Embedded analytics database that chews through CSV/Parquet files at silly speed — ideal for exploring ML datasets locally.
Advanced & research advanced 6

Theory, current literature, and how the machinery underneath actually works — including the math behind the image generators on the AI Art page.

Stanford CS231n (vision) & CS224n (NLP) free advanced — Full university lecture series with notes and assignments, free on YouTube. CS224n covers transformers and LLMs in depth.
Deep Learning Book — Goodfellow, Bengio, Courville free advanced — The standard theory text, free in full HTML. Dense; best used as a reference alongside a course.
The Illustrated Stable Diffusion — Jay Alammar free intermediate — The clearest visual explanation of how diffusion image models work — the theory companion to the AI Art page.
What are Diffusion Models? — Lilian Weng free advanced — The rigorous mathematical treatment of diffusion, when you want the full derivation.
ARENA — Alignment Research Engineer Accelerator free advanced — Open curriculum on mechanistic interpretability, RL, and LLM evals — the practical route into safety research.
Papers With Code free advanced — Current research ranked by benchmark, each paper linked to its implementation. How to stay current after the courses run out.
Microsoft ecosystem
Copilot in Excel, Word, PowerPoint & more →

A dedicated page of free playlists and Microsoft Learn paths for AI inside the Office apps most workplaces already run.

How to use this page

The field moves fast but the fundamentals don't. Start at your tier and finish things — the classic failure mode is collecting resources instead of completing one. Generative image and video tools live on the AI Art page; the theory behind them is here under Advanced.